Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
The members of the Centre for the Mathematical Modelling of Infectious Diseases (CMMID) nCoV working group are listed at the end of the article.
Euro Surveill. 2020 Feb;25(5). doi: 10.2807/1560-7917.ES.2020.25.5.2000080.
We evaluated effectiveness of thermal passenger screening for 2019-nCoV infection at airport exit and entry to inform public health decision-making. In our baseline scenario, we estimated that 46% (95% confidence interval: 36 to 58) of infected travellers would not be detected, depending on incubation period, sensitivity of exit and entry screening, and proportion of asymptomatic cases. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers.
我们评估了在机场进出口对 2019-nCoV 感染进行热乘客筛查的效果,为公共卫生决策提供信息。在我们的基本情况下,根据潜伏期、进出口筛查的敏感性和无症状病例的比例,我们估计 46%(95%置信区间:36 至 58)的受感染旅行者将无法被发现。机场筛查不太可能发现足够比例的 2019-nCoV 受感染旅行者,从而无法避免受感染旅行者的入境。
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